We operate as an extension of your team, deeply aligned to your brand and goals, while you maintain visibility, insight, and approval at key moments. Our responsibility is execution. Yours is confidence that your customers are receiving exceptional, consistent experiences without adding operational lift to your organization.
Start a Conversation See how we do itMost AI initiatives stall after launch. Models don’t fail. Operations do. Without ongoing ownership for tuning, monitoring, governance, and performance, teams are left managing systems they were never staffed or trained to run.
AI answers calls, but who owns the outcomes? When AI performance degrades, escalations spike, or edge cases appear, responsibility is often fragmented across vendors, tools, and internal teams, leaving no one truly accountable for results.
AI improves fastest when paired with human judgment. But most organizations lack a structured way for frontline insight to inform AI behavior, creating a disconnect between real customer interactions and system improvements.
The messy middle is everything between a successful launch and an AI solution that keeps getting better: the design, development, deployment, daily monitoring, model retraining, KPI reviews, and the edge cases nobody planned for. Most vendors skip it. We built our entire model around it.
Brand decisions, approvals, and strategy
Design, development, deployment, daily monitoring, model retraining, KPI reviews, escalation management, and everything in between.
Our managed services model is built around a simple principle: AI only delivers value when someone owns it end-to-end. We take responsibility for performance, reliability, and continuous improvement, not just implementation.
We don’t hand you a platform, a playbook, or a roadmap and step away. Humach designs, deploys, operates, and continuously improves your solution as a live production system. From day one, your AI, workflows, and CX operations are actively managed, not left to drift after go-live.
AI, CCaaS, CRM, integrations, live agents, and digital agents are treated as one system, not separate initiatives. Our teams operate across technology and operations with a single set of KPIs, governance rhythms, and accountability, eliminating the handoffs that cause performance gaps.
AI Whisperers aren’t an add-on, they’re built into the operating model. These upskilled experts sit between real customer interactions and engineering, translating frontline insight into targeted improvements that increase accuracy, safety, and customer trust over time.
Customer behavior changes. Products change. Policies change. Your AI has to keep up. We run structured feedback loops, and testing cycles so performance improves continuously, without creating operational chaos or surprise changes.
You stay in control of brand, priorities, and approvals. We take on the day-to-day execution, monitoring, tuning, reporting, and governance. Your internal teams get visibility and confidence without having to staff or manage a new operating function.
Our model is designed to launch strong, operate reliably, and improve continuously with human and machine intelligence working together from day one.
We start by establishing clear ownership, governance, KPIs, and compliance requirements. This includes identifying how AI Whisperers will be embedded into the program, either by upskilling live agents or assigning dedicated AI Whisperers trained on your live‑agent curriculum and workflows. Success metrics like CSAT, containment, handle time, escalation rules, and regulatory guardrails are defined early and guide every decision that follows.
We analyze real call drivers, high‑volume intents, and the interactions your live agents handle every day. AI Whisperers participate in this discovery to ensure the solution reflects how customers actually behave, not not how we assume they will. Together, we define which interactions are right for automation, what the digital agent must know, and how it should sound and behave to represent your brand. Institutional knowledge, whether from existing agents or trained Whisperers, directly shapes the design.
Our AI Engineering team builds AI workflows, configures behavior, and integrates with your existing systems and platforms. AI Whisperers are involved during this phase to validate logic, edge cases, and escalation paths against real operational scenarios. Your IT and CX teams stay informed and aligned, while we handle execution, integrations, and readiness without adding operational burden.
Before your digital agent takes a single live call, it’s stress‑tested. AI Whisperers and Engineers run hundreds of simulated interactions including edge cases, breakdowns, escalations, and confused callers and use that information to tune responses and workflows. In parallel, we use AI‑based evaluation models to score accuracy, policy adherence, and response quality at scale. You participate in testing and provide final sign‑off before anything reaches production.
Go‑live is an actively managed event. We confirm dashboards, escalation paths, and governance controls, and launch with human and AI monitoring in place. From the first live call, we’re tracking containment, drop‑off points, sentiment, and policy adherence and intervene immediately if adjustments are needed.
This is the engine that most vendors skip. Our AI Whisperers review interactions daily and use frontline insight to provide feedback for the engineering team to correct failures, refine workflows, and improve customer outcomes. At the same time, AI‑based evaluation continuously analyzes conversations at scale to identify patterns humans can’t catch alone. You receive regular performance reviews tied to your KPIs, with clear recommendations, prioritized improvements, and transparent outcomes. A strong launch is the starting line. Continuous improvement is the differentiator.
We’re not technologists who’ve never set foot in a contact center. We’re contact center professionals who built the technology we always wished we had.
-Jennifer Lundberg
Anyone can resell a platform or hand you a roadmap. Humach brings something far harder to replicate: Decades of experience operating customer experience and contact centers at scale, combined with deep technical expertise in the tools that power it.
We’ve been responsible for outcomes, not just implementations, and we built our managed services model to solve the problems we lived ourselves.
Humach Managed Services was designed by people who have been accountable for real performance in live environments. Everything we do reflects what we wished vendors had owned, especially after launch.
We don’t measure success by tickets closed or features deployed. We’re measured against the metrics that matter to you: customer effort, resolution, reliability, and cost to serve.
We work across leading AI, CCaaS, and enterprise platforms, selecting and configuring the right stack for your needs. Decisions are driven by outcomes and fit, not resale incentives or demo scripts.
As your needs evolve, your Humach team evolves with you. New capabilities, new channels, new challenges without having to rebuild from scratch every time.
If you’re tired of babysitting platforms, juggling vendors, or wondering who owns performance after launch, we should talk. Start with a discovery session. An honest conversation about where you are today, what’s getting in the way, and what it would look like to have a team that truly runs this for you.
Managed services shouldn’t add work. It should remove it.
